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java.lang.Object org.apache.commons.math3.distribution.AbstractRealDistribution org.apache.commons.math3.distribution.ChiSquaredDistribution
public class ChiSquaredDistribution
Implementation of the chi-squared distribution.
Field Summary | |
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static double |
DEFAULT_INVERSE_ABSOLUTE_ACCURACY
Default inverse cumulative probability accuracy |
Fields inherited from class org.apache.commons.math3.distribution.AbstractRealDistribution |
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random, randomData, SOLVER_DEFAULT_ABSOLUTE_ACCURACY |
Constructor Summary | |
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ChiSquaredDistribution(double degreesOfFreedom)
Create a Chi-Squared distribution with the given degrees of freedom. |
|
ChiSquaredDistribution(double degreesOfFreedom,
double inverseCumAccuracy)
Create a Chi-Squared distribution with the given degrees of freedom and inverse cumulative probability accuracy. |
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ChiSquaredDistribution(RandomGenerator rng,
double degreesOfFreedom,
double inverseCumAccuracy)
Create a Chi-Squared distribution with the given degrees of freedom and inverse cumulative probability accuracy. |
Method Summary | |
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double |
cumulativeProbability(double x)
For a random variable X whose values are distributed according
to this distribution, this method returns P(X <= x) . |
double |
density(double x)
Returns the probability density function (PDF) of this distribution evaluated at the specified point x . |
double |
getDegreesOfFreedom()
Access the number of degrees of freedom. |
double |
getNumericalMean()
Use this method to get the numerical value of the mean of this distribution. |
double |
getNumericalVariance()
Use this method to get the numerical value of the variance of this distribution. |
protected double |
getSolverAbsoluteAccuracy()
Returns the solver absolute accuracy for inverse cumulative computation. |
double |
getSupportLowerBound()
Access the lower bound of the support. |
double |
getSupportUpperBound()
Access the upper bound of the support. |
boolean |
isSupportConnected()
Use this method to get information about whether the support is connected, i.e. |
boolean |
isSupportLowerBoundInclusive()
Whether or not the lower bound of support is in the domain of the density function. |
boolean |
isSupportUpperBoundInclusive()
Whether or not the upper bound of support is in the domain of the density function. |
Methods inherited from class org.apache.commons.math3.distribution.AbstractRealDistribution |
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cumulativeProbability, inverseCumulativeProbability, probability, probability, reseedRandomGenerator, sample, sample |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY
Constructor Detail |
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public ChiSquaredDistribution(double degreesOfFreedom)
degreesOfFreedom
- Degrees of freedom.public ChiSquaredDistribution(double degreesOfFreedom, double inverseCumAccuracy)
degreesOfFreedom
- Degrees of freedom.inverseCumAccuracy
- the maximum absolute error in inverse
cumulative probability estimates (defaults to
DEFAULT_INVERSE_ABSOLUTE_ACCURACY
).public ChiSquaredDistribution(RandomGenerator rng, double degreesOfFreedom, double inverseCumAccuracy)
rng
- Random number generator.degreesOfFreedom
- Degrees of freedom.inverseCumAccuracy
- the maximum absolute error in inverse
cumulative probability estimates (defaults to
DEFAULT_INVERSE_ABSOLUTE_ACCURACY
).Method Detail |
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public double getDegreesOfFreedom()
public double density(double x)
x
. In general, the PDF is
the derivative of the CDF
.
If the derivative does not exist at x
, then an appropriate
replacement should be returned, e.g. Double.POSITIVE_INFINITY
,
Double.NaN
, or the limit inferior or limit superior of the
difference quotient.
x
- the point at which the PDF is evaluated
x
public double cumulativeProbability(double x)
X
whose values are distributed according
to this distribution, this method returns P(X <= x)
. In other
words, this method represents the (cumulative) distribution function
(CDF) for this distribution.
x
- the point at which the CDF is evaluated
x
protected double getSolverAbsoluteAccuracy()
getSolverAbsoluteAccuracy
in class AbstractRealDistribution
public double getNumericalMean()
k
degrees of freedom, the mean is k
.
Double.NaN
if it is not definedpublic double getNumericalVariance()
2 * k
, where k
is the number of degrees of freedom.public double getSupportLowerBound()
inverseCumulativeProbability(0)
. In other words, this
method must return
inf {x in R | P(X <= x) > 0}
.
public double getSupportUpperBound()
inverseCumulativeProbability(1)
. In other words, this
method must return
inf {x in R | P(X <= x) = 1}
.
Double.POSITIVE_INFINITY
.public boolean isSupportLowerBoundInclusive()
getSupporLowerBound()
is finite and
density(getSupportLowerBound())
returns a non-NaN, non-infinite
value.
public boolean isSupportUpperBoundInclusive()
getSupportUpperBound()
is finite and
density(getSupportUpperBound())
returns a non-NaN, non-infinite
value.
public boolean isSupportConnected()
true
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